A Novel Method for Evaluating Diversity of Stand Structure Based on Relationship of Adjacent Trees

Abstract Background Improving the diversity and complexity of stand structure is the basis for maintaining and increasing forest ecosystem biodiversity. Measures of stand structural diversity is important for predicting stand growth and evaluating forest management activities. Based on the relationship of adjacent trees, we present a new method for the quantitative analysis of stand structure diversity that allows comparison of stand structural heterogeneity between different stands and forest types and to quantify the impact of forest management on structural diversity. Method: The diversity of structural unit types was defined and then we derive a new index of forest structural diversity () according to the additivity principle of Shannon-Weiner index. The effectiveness and sensitivity to management were verified by sixteen field survey samples in different locations and six different simulated management datasets based on Pinus koraiensis broad-leaved forest survey sample. Results (1) The mountain rainforest in Hainan had the highest \({{S}^{\text{'}}}_{D}\) value at 5.287, followed by broad-leaved Korean pine forest in Jiaohe (2), Jiaohe (1) and oak broadleaved mixed natural forest in Xiaolongshan (2), with values of 5.144, 5.014 and 5.006, respectively. The \({{S}^{\text{'}}}_{D}\) values of plantations and natural pure forest were lower. (2) Different thinning methods and intensities reduced \({{S}^{\text{'}}}_{D}\) compared with no treatment and magnitude of the with the differences were greater as thinning intensity increased. The \({{S}^{\text{'}}}_{D}\) value of thinning from above decreased more than thinning from below at the same thinning intensity. Conclusion The\({{S}^{\text{'}}}_{D}\) well describes differences in stand structural diversity of different forest types and allows comparison of stand structural heterogeneity. It is also sensitive to forest management activities and to quantify the impact of forest management on structural diversity. The application of this new index \({{S}^{\text{'}}}_{D}\) could greatly facilitate forest management and monitoring.